In the inventory decision support system, IDSS, the automatic selecting mode of inventory control relies on reasonable classification of commodity. Since rational application of inventory control model rests with so many factors, such as demand, supply and etc., present ABC and CVA classification methods are obviously insufficient to solve commodities classification problems. In this paper, least squares Support Vector Machines, SVM, are firstly adopted to construct a classifier solving inventory goods classification. It shows higher classification speed and reasonable classification result in the practical running. Further more, this method solved the dynamic classification problem.
Mode Classification Based on Decision-Tree-Based Support Vector Machine in the Inventory Control
First International Conference on Transportation Engineering ; 2007 ; Southwest Jiaotong University, Chengdu, China
2007-07-09
Conference paper
Electronic Resource
English
Mode Classification Based on Decision-Tree-Based Support Vector Machine in the Inventory Control
British Library Conference Proceedings | 2007
|Double Mode Control Based on Least Squares Support Vector Machine
British Library Online Contents | 2011
|Data classification with support vector machine and generalized support vector machine
American Institute of Physics | 2017
|British Library Conference Proceedings | 2003
|